Journal of Tropical Oceanography ›› 2021, Vol. 40 ›› Issue (6): 41-51.doi: 10.11978/2020141CSTR: 32234.14.2020141

• Marine Hydrology • Previous Articles     Next Articles

Reconstructing salinity profile using temperature profile and sea surface salinity

HE Zikang1,2(), WANG Xidong1,2,3(), CHEN Zhiqiang1,2, FAN Kaigui1,2   

  1. 1. Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Nanjing 210098, China
    2. College of Oceanography, Hohai University, Nanjing 210098, China
    3. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China
  • Received:2020-12-01 Revised:2021-03-05 Online:2021-11-10 Published:2021-03-15
  • Contact: WANG Xidong E-mail:181310010013@hhu.edu.cn;xidong_wang@hhu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(4177060056)

Abstract:

A large number of marine observations contain only temperature profiles, but not salinity profiles that are important for understanding ocean dynamics. To construct salinity profiles, we use regression analysis methods to establish relationship of ocean salinity with historical ocean temperature, longitude, latitude, and satellite-based sea surface salinity (SSS) in the Bay of Bengal. The results of different inversion methods are then tested and evaluated. We find that without introducing SSS, the best reconstruct model is using temperature, namely, using the secondary items of temperature with longitude and latitude to determine the regression model. However, the introduction of SSS can further improve the inversion results. By comparing the reconstructions with the observations, we show that the steric height error calculated by the salinity profile inversion is more than 2.0 cm, while the error calculated after introducing SSS is less than 1.5 cm. The introduction of SSS can truly reflect the vertical structure and internal variation characteristics of ocean salinity profile. It can not only capture the SSS signal that has an important influence on the upper mixing layer, but also reflect the seasonal change of salinity on the thermocline and the seasonal change of the barrier layer. The inversion results are compared with the climatology, and the observed water mass is analyzed, showing that compared with the climatology, the inversion can better represent the variation characteristics of the surface water mass. However, below the mixing layer, there is no significant difference between the inversion and climatology.

Key words: sea surface salinity, salinity profile reconstruction, temperature profile,steric height, water mass, Bay of Bengal

CLC Number: 

  • P731.1